Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Doris-Labs/sales-skills --skill prospectinggit clone --depth 1 https://github.com/Doris-Labs/sales-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/doris-labs/sales-skills/prospecting)<a href="https://agentmods.dev/skills/doris-labs/sales-skills/prospecting"><img src="https://agentmods.dev/badge/skills/doris-labs/sales-skills/prospecting/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/doris-labs/sales-skills/prospecting"><img src="https://agentmods.dev/badge/skills/doris-labs/sales-skills/prospecting.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00070 | $0.01609 |
| Opus 5 | $0.00035 | $0.00805 |
| Sonnet 5 | $0.00014 | $0.00322 |
| Haiku 4.5 | $0.00007 | $0.00161 |
Grade A, and why
prospecting scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prospecting
Purpose
Turn a vague "go find more pipeline" into a ranked target list: accounts that match your ICP, scored on fit and intent, ordered by what just happened (the trigger), each with a one-line "why now" and the persona to open with.
Inputs
- Your ICP definition (or enough to build one: industry, size, geo, tech, motion)
- What "good" looks like — your best-fit closed-won accounts to pattern-match against
- Any existing account universe (CRM, territory, list) to work or de-dupe against
- How many targets you want and over what window
Method
-
Define / sharpen the ICP filter. Lock the hard filters first — only accounts that pass all of these belong on the list:
- Firmographic: industry / vertical, employee count, revenue band, geography.
- Technographic: tools they run that imply fit (CRM, CI, data stack, a competitor's product).
- Motion: B2B/B2C, sales-led vs PLG, deal size band you can actually win.
- Disqualifiers: sizes/industries/regions you lose in — exclude up front. Anchor each filter to evidence from won deals, not opinion.
-
Score each account: Fit × Intent. Two independent axes, then combine.
- Fit (0–5) — how closely the account resembles your won-deal profile:
5near-twin of a won account ·3ICP match, no proof yet ·0fails a hard filter (drop). - Intent (0–5) — observable buying signals, weighted by recency: hiring for the pain you solve, leadership change, funding/M&A, expansion, tech adoption/churn, content/event engagement, inbound touch.
- Priority score = Fit × Intent. Fit-but-no-intent = nurture; intent-but-no-fit = ignore; high-both = work now. Multiplying (not adding) kills the no-fit-high-noise traps.
- Fit (0–5) — how closely the account resembles your won-deal profile:
-
Trigger-based prioritization. Among high scorers, order by the freshest, most actionable trigger — a trigger is the reason the email lands this week:
- Tier A (act now): new exec in the buying role, funding round, layoffs/reorg in your function, public initiative matching your value, switched off a competitor.
- Tier B (this month): hiring spree in target dept, new product launch, expansion/new market.
- Tier C (passive): tech-stack fit only, lookalike to a won account, old inbound. Recency decays the trigger — a 6-month-old funding round is Tier C.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 114 lines · 70 tokens per session scan A 879be2fdbdc3
prospecting is a skill published in the GitHub repository Doris-Labs/sales-skills (3 stars, last pushed 3mo ago), licensed MIT. It adds 70 tokens to every session and 1,609 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
lynqu
Entry point for the Lynqu sales suite — describe any sales situation and it composes the right skills across capture, outreach, quoting and reporting. Requires the Lynqu MCP server connected.
lynqu-sales-playbook
Turn a written sales playbook into a live Lynqu pipeline — contacts, timed tasks, follow-up templates, the playbook attached to each lead, and stage rules that deliver the prep at the right moment.
lynqu-card-studio
Create and update Lynqu digital business cards — contact info, social links, services, template, palette — and check card views, scans and shares. Requires the Lynqu MCP server connected.
lynqu-competitors
Build a battlecard for the incumbent on a Lynqu deal — switching cost, wedge, objections and honest answers — written back to the lead. Requires the Lynqu MCP server.
lynqu-contacts
Map the buying committee on an account — economic buyer, champion, blocker — and write it into Lynqu as contacts and participants. Requires the Lynqu MCP server.
lynqu-deal-desk
Price a Lynqu deal and draft the quote — browse the price book, put priced lines on a deal, then produce a draft quote for a human to send. Requires the Lynqu MCP server connected.